Systems and methods for monitoring the circulatory system

ABSTRACT

In accordance with embodiments of the present disclosure, a user-platform apparatus, such as a bodyweight sensing scale, includes a heart/cardiogram sensor which is used to detect heart and vascular characteristics of a user, and provide a cardiogram output indicative of the detected cardiovascular characteristics. The cardiogram output can be used for various purposes, such as detecting arterial stiffness and/or aging.

RELATED DOCUMENTS

This patent document is a continuation under 35 U.S.C. §120 of U.S.patent application Ser. No. 14/691,965 filed on Apr. 21, 2015 (U.S. Pat.No. 9,241,637), which is a divisional of U.S. patent application Ser.No. 13/982,185 filed on Jul. 26, 2013 (U.S. Pat No. 9,011,346), which isthe national stage filing under 35 U.S.C. §371 of InternationalApplication No. PCT/US2012/022664 (WO 2012/103296 A2) filed on Jan. 26,2012, which claims the benefit under 35 U.S.C. §119(e) of U.S.Provisional Patent Application Ser. No. 61/436,740 filed on Jan. 27,2011, and entitled “Systems and Methods for Assessment of ArterialStiffness and Management of Hypertension;” and to U.S. ProvisionalPatent Application Ser. No. 61/475,887 filed on Apr. 15, 2011, andentitled “Systems and Methods for Monitoring the Circulatory System;”U.S. patent application Ser. No. 13/982,185 (U.S. Pat. No. 9,01,346)also relates to U.S. patent application Ser. No. 12/579,264 filed onOct. 14, 2009 (U.S. Pat. No. 8,870,780), and entitled “Systems andMethods for Monitoring Heart Function;” which claims the benefit of U.S.Provisional Patent Application No. 61/105,696 filed on Oct. 15, 2008,which included five appendices (A through E) that provide example andexperimental results for use with various embodiments of the presentdisclosure. These applications and documents, and to the extent thatthese documents cite various references, are fully incorporated hereinby reference.

OVERVIEW

This disclosure relates generally to monitoring of circulatory function,and in specific instances, to systems and methods for detection ofarterial stiffening and central arterial blood pressure.

Hypertension is, overall, the major contributor to the risks ofcardiovascular disease (CVD), attributable to 54% of stroke and 47% ofischemic heart disease (IHD) cases worldwide. In the United Statesalone, hypertension affects well over one-quarter of the populationprimarily as a consequence of the population becoming older and moreobese. Proper management of hypertension can lower CVD risksignificantly. However, the underlying causes of chronically elevatedblood pressure are many, with limited number of tests available todiagnose and monitor hypertensive change.

Another circulatory problem associated with hypertension and CVD risk isarterial aging, which is a hardening of the arterial wall and isconsidered a primary cause of a host of cardiovascular disorders andcomplications, including increased blood pressure, left ventricularhypertrophy, myocardial infarction, stroke and renal failure.

SUMMARY

The present disclosure is directed to systems, methods and approachesfor monitoring of vascular stiffness and central blood pressure. Thepresent disclosure is exemplified in a number of implementations andapplications including those presented below, which are commensuratewith certain claims included with this patent document.

Embodiments of the present disclosure are directed towards the use ofballistocardiography, impedance cardiography, photoplethysmography, andperipheral blood pressure measurements to measure arterial aging(vascular stiffness) and central arterial blood pressure. Arterial agingis a hardening of the arterial wall and is considered a primary cause ofa host of cardiovascular disorders and complications, includingincreased blood pressure, left ventricular hypertrophy, myocardialinfarction, stroke and renal failure. Various embodiments of the presentdisclosure recognize that aortic stiffness and thickening of thearterial walls (atherosclerosis) appear closely related.

Aspects of the present disclosure are also directed toward measuring, ata single location (e.g., the feet, using a modified bathroom scale),multiple signals that each have their origin at two different locationsin the body. This can be particularly useful for determining arterialstiffness. For instance, one signal can originate at the aortic arch forthe ballistocardiogram, and one signal can originate at the feet for thefoot photoplethysmogram (PPG). This aspect can facilitate themeasurement of the relative timings of these two signals (e.g., tocompute arterial pulse wave velocity), since, for example, there is noneed to accurately place highly-sensitive probes at multiple locationson the body. Such aspects can also be useful for improvedreproducibility of pulse wave velocity measurements, e.g., due to thesensor types and their arrangements for self-measurement.

According to an example embodiment, a system acquires BCG(ballistocardiogram) data from a user. The system includes a BCG capturedevice, a secondary sensor and a processor circuit. The BCG capturedevice includes a heart and vascular characteristic sensor thatcaptures, from the user, a BCG signal indicative of at least one ofphysical movement and mechanical output of the user's proximal aorta.The secondary sensor detects the blood pressure pulse travel time at theuser's feet, to determine a characteristic of the user's distal arterialstiffness, and then provides an output characterizing the detectedindication. The processor circuit uses the sensor outputs to determinebest estimates of the user's overall circulatory function and togenerate an output result indicative of a user's arterial condition.

Consistent with another example embodiment of the present disclosure, asystem acquires BCG (ballistocardiogram) data from a user. The systemincludes a BCG capture device, a plurality of secondary sensors and aprocessor circuit. The BCG capture device includes a heart and vascularcharacteristic sensor that captures, from the user, a BCG signalindicative of at least one of physical movement and mechanical output ofthe user's proximal aorta. The secondary sensors detects the bloodpressure pulse travel time at the user's feet and hands, to determinedifferential characteristics of the user's arterial stiffness alongdifferent branches, and then provides an output characterizing thedetected indications. The processor circuit uses the sensor outputs todetermine best estimates of the user's overall circulatory functionalong different arterial branches and also estimates arterial stiffnessof intermediate segments to generate an output result indicative of auser's arterial condition.

Consistent with another example embodiment of the present disclosure, asystem acquires impedance cardiogram (ICG) data from a user. The systemincludes an ICG capture device, a secondary sensor and a processorcircuit. The ICG capture device includes a sensor that captures, fromthe user, an ICG signal indicative of at least one of physical movementand mechanical output of the user's proximal aorta. The secondary sensordetects the blood pressure pulse travel time at the user's feet, todetermine a characteristic of the user's distal arterial stiffness, andthen provides an output characterizing the detected indication. Theprocessor circuit uses the sensor outputs to determine best estimates ofthe user's overall circulatory function and to generate an output resultindicative of a user's arterial condition.

Consistent with another example embodiment of the present disclosure, asystem/method provides ballistocardiogram (BCG) measurements (e.g., inreal-time) from a user standing on a BCG capture device. A force sensoris arranged to capture a signal indicative of the physical movementand/or mechanical output of the heart of the user while the user isstanding on the device. A second specific sensor type (e.g., ECG,accelerometer, geophone, displacement, electromyogram or video imagingdevice) provides additional information about the captured signal, whichmay be indicative of noise and/or interference present in the BCGmeasurement, or of other characteristics of the user. A processor usesthe second sensor signal to process the captured signal, such as tofilter or gate (e.g., weight or eliminate aspects of) a captured BCGrecording, and provide user diagnostics.

In some implementations, a captured BCG recording is gated to aweight-derived motion signal or eliminate segments of the recording thatcontain higher than usable noise or interference levels (e.g., foraveraging algorithms). For example, regions of higher noise can be givenproportionally lower weighting in weighted ensemble averagingalgorithms, such as maximum likelihood averaging.

Aspects of the present disclosure are directed towards detection ofmotion artifacts in BCG signals using a secondary sensor. In somesituations, motion of a patient leads to an unacceptable number of noisysegments in the BCG. The BCG force signal level is on the order of a fewNewtons in magnitude. Body movement can easily introduce noise artifactsof similar magnitude and orders greater. Noise on the order of the BCGsignal level can be difficult to detect from the BCG signal alone.

Another example embodiment is directed to a system for providing BCG(ballistocardiogram) data from a user. The system includes a BCG capturedevice, a secondary sensor and a processor circuit. The BCG capturedevice includes a heart-characteristic sensor that captures, from theuser, a BCG signal indicative of at least one of physical movement andmechanical output of the user's heart. The secondary sensor detects anindication of at least one of noise source present in the BCG signal anda physiologic characteristic of the user (e.g., a heart characteristicand/or a noise-based characteristic), and provides an outputcharacterizing the detected indication. The processor circuit uses thesecondary sensor output to process the captured BCG signal and generatean output BCG signal indicative of a condition of the user's heart.

Aspects of the present disclosure are also directed toward a system forquantifying blood pressure differences between the brachial artery andaorta. The system includes a BCG capture device, a secondary PPG sensorat a point along the arm (e.g. brachial, radial, or finger), and anotherPPG sensor at a point distal of the descending aorta (e.g. the feet).The system uses the vascular stiffness measurements along the arterialtrack to determine the brachial and central pressure differences. Thesystem includes a device (e.g. an automated brachial blood pressurecuff, ambulatory blood pressure monitor, finger sphygmomanometer, etc.)to measure peripheral blood pressure. The central aortic blood pressureis then determined, using the peripheral blood pressure measurement inconjunction with the arterial stiffness measurements from the system.

The above summary of the present disclosure is not intended to describeeach illustrated embodiment or every implementation of the presentdisclosure.

BRIEF DESCRIPTION OF THE FIGURES

The disclosure may be more completely understood in consideration of thedetailed description of various embodiments of the disclosure thatfollows in connection with the accompanying drawings, in which:

FIG. 1A depicts a diagram of a weighing scale (e.g., bathroom scale)that can capture ballistocardiographic (BCG) and photoplethysmographic(PPG) signals, consistent with embodiments of the present disclosure;

FIG. 1B depicts a diagram of a weighing scale (e.g., bathroom scale)that includes a finger PPG sensor to acquire an additional timepoint T3,consistent with embodiments of the present disclosure;

FIG. 2 illustrates an algorithm for deriving intermediate arterialstiffness values from the combined central+peripheral measurements ofBCG and foot PPG, utilizing a finger PPG signal, consistent withembodiments of the present disclosure;

FIG. 3 shows a circuit for acquiring BCG signals from a commercialweighing scale, consistent with another example embodiment of thepresent disclosure;

FIG. 4 depicts a diagram of a hand-to-hand impedance cardiogram and aweighing scale (e.g., bathroom scale) that can capturephotoplethysmographic (PPG) signals, consistent with embodiments of thepresent disclosure;

FIG. 5 illustrates a computer simulation result for the timingrelationship of the central aortic force (CAF) waveform to the aorticpressure pulse, consistent with embodiments of the present disclosure;

FIG. 6 depicts a timing relationship of the BCG to the carotid arterypulse, consistent with embodiments of the present disclosure;

FIG. 7 depicts a histogram of the time difference (in seconds) betweenthe I-wave of the ballistocardiogram and the start of the carotidpressure pulse from multiple test subjects, consistent with embodimentsof the present disclosure;

FIG. 8 depicts the timings from the ECG R-wave of the BCG I-wave andcarotid artery pulse of an individual over a four month period,consistent with embodiments of the present disclosure for the T1 timing;

FIG. 9 depicts the comparison of carotid versus BCG-based pulse transittimings (PTT=T2−T1) where T2 is measured at the foot of an individualover a four month period, consistent with embodiments of the presentdisclosure;

FIG. 10 illustrates the relative timing relationship of the BCG to theperipheral PPG signals taken at the finger and toe, consistent withembodiments of the present disclosure;

FIG. 11 depicts posture-dependent pulse transit timings for a singlesubject in the sitting, standing, and lying down positions;

FIG. 12 depicts a plot of the standing pulse wave velocity versus theage (in years) of multiple subjects, consistent with embodiments of thepresent disclosure;

FIG. 13 shows exemplary time traces of beat-to-beat systolic bloodpressure (SBP) (units in mmHg, top) and beat-to-beat standing PWVmeasurements (units in meters per second, bottom) estimated with BCG andfoot PPG signals obtained from a modified bathroom scale, consistentwith embodiments of the present disclosure;

FIG. 14A shows a block diagram of a system and approach for detectingcardiovascular function using BCG and secondary sensors for BCG signalenhancement, consistent with another example embodiment of the presentdisclosure;

FIG. 14B shows a block diagram of a system and approach for detectingcardiovascular function using BCG and a handlebar ECG sensor as thesecondary sensor for BCG signal enhancement, consistent with anotherexample embodiment of the present disclosure;

FIG. 14C shows a block diagram of a system and approach for detectingcardiovascular function using BCG and an embedded motion sensorcontained in a modified weighing scale and ECG as secondary sensors forBCG signal enhancement, consistent with another example embodiment ofthe present disclosure;

FIG. 15 depicts a method to estimate central pressures using aperipheral blood pressure measurement, pulse wave velocity measurementsand information of the user, consistent with embodiments of the presentdisclosure;

FIG. 16A depicts central systolic blood pressure for multiple subjects(obtained with a SphygmoCor arterial tonometer from AtCor Medical);

FIG. 16B is a plot of the standing pulse wave velocity (consistent withembodiments of the present disclosure) versus the central systolic bloodpressure for multiple subjects (obtained with a SphygmoCor arterialtonometer from AtCor Medical);

FIG. 17A depicts central pulse pressure for multiple subjects (obtainedwith a SphygmoCor arterial tonometer from AtCor Medical);

FIG. 17B is a plot of the standing pulse wave velocity (consistent withembodiments of the present disclosure) versus the central pulse pressurefor multiple subjects (obtained with a SphygmoCor arterial tonometerfrom AtCor Medical);

FIG. 18A depicts measured systolic differences between a peripheralblood pressure and aortic central pressure, consistent with embodimentsof the present disclosure; and

FIG. 18B depicts measured central systolic pressure differences obtainedwith embodiments of the present disclosure and with central pressuremeasurements obtained from a SphygmoCor arterial tonometer from AtCorMedical, consistent with embodiments of the present disclosure.

While the disclosure is amenable to various modifications andalternative forms, examples thereof have been shown by way of example inthe drawings and will be described in detail. It should be understood,however, that the intention is not to limit the disclosure to theparticular embodiments shown and/or described. On the contrary, theintention is to cover all modifications, equivalents, and alternativesfalling within the spirit and scope of the disclosure.

DETAILED DESCRIPTION

Various embodiments of the present disclosure have been found to beparticularly useful in connection with monitoring heart and vascularfunction (e.g., to determine cardiovascular health of a patient) in amanner that facilitates home use by the patient. While the presentdisclosure is not necessarily limited to such applications, variousaspects of the disclosure may be appreciated through a discussion ofvarious examples using this context.

Aspects of the present disclosure are directed to detecting the heartand vascular function of a user with a sensor that detects weight and/orweight variances of a user. A processing arrangement or processorcircuit is configured (e.g., with an algorithm/transform) to determineheart and vascular function characteristics of the user based upon thedetected weight and/or weight variances. The processing arrangement usesdata from one or more additional sensors as a parameter of thealgorithm/transform. In connection with these example aspects, it hasbeen discovered that such implementations can be particularly useful forproducing unexpectedly practical and reliable central blood pressure andvascular stiffness measurements.

Embodiments of the present disclosure are directed toward therealization that measurements of arterial stiffness in thestanding/upright position are beneficial compared to measurementsobtained in the lying down and seated position (FIG. 11). The standingposition is believed to represent a measurement of a nearly full-bodylength arterial stiffness measurement, thus characterizing a largeportion of anatomy associated with the largest contribution of pressurewave reflections to the heart.

Embodiments of the present disclosure are directed towards the use ofBCG measurements to measure arterial aging (vascular stiffness).Arterial aging is a hardening of the arterial wall and is considered aprimary cause of a host of cardiovascular disorders and complications,including increased blood pressure, left ventricular hypertrophy,myocardial infarction, stroke and renal failure. Various embodiments ofthe present disclosure recognize that aortic stiffness and thickening ofthe arterial walls (atherosclerosis) appear closely related.

Aspects of the present disclosure are also directed toward measuring, ata single location (e.g., the feet, using a modified bathroom scale),multiple signals that each have their origin at two different locationsin the body. For instance, one signal can originate at the aortic archfor the ballistocardiogram, and one signal can originate at the feet forthe toe PPG. This aspect can facilitate the measurement of the relativetimings of these two signals (e.g., to compute pulse wave velocity),because, for example, here, there is no need to accurately placehighly-sensitive probes at multiple locations on the body, as in thecase of applanation tonometry. Such aspects can also be useful forimproved reproducibility of pulse wave velocity measurements, e.g., dueto the ease of the measurement setup procedure.

Aspects of the present disclosure are directed towards the use of BCGmeasurements to measure arterial aging (vascular stiffness). Arterialaging is a hardening of the arterial wall and is considered a primarycause of a host of cardiovascular disorders and complications, includingincreased blood pressure, left ventricular hypertrophy, myocardialinfarction, stroke and renal failure, which is discussed in (O'Rourke etal., 2002). Aortic stiffness and thickening of the arterial walls(atherosclerosis) appear closely related as discussed in (van Popele etal., 2001).

Chronically increased blood pressure (hypertension) is a conditiondirectly linked to numerous cardiovascular diseases and increasedmortality rate, if left untreated. Hypertension can be controlled andnormotensive levels can be achieved with pharmaceutical agents (e.g.,beta blockers, calcium channel blockers, ACE inhibitors, and diuretics)that act upon specific pathways to lower vascular resistance to bloodflow, reduction in pressure wave reflections in systole, orcontractility and that may reduce cardiovascular disease complicationsand increase life expectancy. The success of antihypertensive therapyand, presumably, the success of managing cardiovascular disease risk,have traditionally been determined by measurements of the peripheralblood pressure (e.g., brachial blood pressure at the arm or radial bloodpressure at the wrist) where diastolic and systolic values are assessedas the primary parameters to determine the success of theantihypertensive therapy.

Cardiovascular studies suggest that the measurement of the central bloodpressure (the aortic pressure pulse) more reliably stratifiescardiovascular disease risk than the measurement of peripheral bloodpressure as discussed in [Safar, 2010; Blacher et al., 1999]. The aortais located between the heart and the major organs, and the aorticpressure pulse wave, rather than the peripheral pressure pulse, is theforce ultimately experienced by the organs. The central pressure maybetter represent the load that is imposed on the organs and theresulting damage. Aberrant central hemodynamic properties that oftendevelop from arterial aging and consequently stiffening of thecardiovascular vessels (arterial vascular stiffness) can, thus,ultimately lead to cardiovascular-induced organ damage and failure.Individuals, who are at risk of developing cardiovascular disease, thus,need to be monitored frequently to improve their chances of successfullymanaging cardiovascular risk.

The detection of changes in arterial elasticity and other hemodynamicproperties can be useful, not only to provide therapeutic benefit toindividuals who are already hypertensive and/or in antihypertensivetreatment, but also to provide prognostic as well as diagnostic benefitto individuals whose blood pressure has not yet reached a level that isconsidered elevated, but who nevertheless are at an increased risk forcardiovascular events.

Aspects of the present disclosure are directed toward devices andmethods that can be useful for both normotensive and hypertensiveindividuals to measure and monitor their central hemodynamic propertiesin a straight forward, yet reliable and quick manner, without the needfor medical supervision or technical assistance.

A measurement of the Carotid-Femoral Pulse Wave Velocity (cfPWV) can beused to quantify aortic stiffness. The carotid artery is used as thefirst time point (T1) representing the pressure pulse of the ascendingaorta and the second time point (T2) at the femoral artery as the end ofartery. The time ΔT=T2−T1 is divided by the distance (D) between themeasurement locations to obtain a value for velocity.

Consistent with the embodiments discussed herein, the T1 timepoint canbe provided by the BCG measure [“BCG T1”] and corresponds to theproximal, or T1 carotid timepoint, while the T2 timepoint can beprovided by the PPG measure [“PPG-toe T2”] and corresponds to the T2distal arterial timepoint. The BCG T1 and PPG-toe T2 timepoints canthereby be used to calculate arterial vascular stiffness.

Arterial stiffness can be estimated by measuring the pulse wave velocity(PWV) along the artery rather than by performing the direct stiffnessmeasurement. The Moens-Korteweg equation relates the wave speed (c) tothe vessel wall elastic modulus (E), wall thickness (t), diameter (D),and blood density (ρ).

$c = \sqrt{\frac{Et}{\rho\; D}}$

Arterial PWV increases with increasing arterial stiffness and is anon-invasive measure to quantify arterial stiffness. Pulse wave velocityis measured as the difference between two recording sites in the line ofpulse travel and the delay between corresponding points on the wave (ofpressure or of flow), where the wavefront is the usual point ofreference in the two waveforms (O'Rourke et al., 2002). The carotid andfemoral arteries can be used as points of measurements to estimateaortic stiffness, where arterial pulse waves are recorded at the carotidartery representing the proximal ascending aorta as well as at thefemoral artery as the more distal artery. The superficial location ofthe carotid and femoral arteries make a non-invasive applanationmeasurement possible.

The time delay between the arrival of a predefined part of the pulsewave, such as the foot (sharp initial systolic upstroke), at these tworeference points can be obtained either by simultaneous measurement orby gating to the peak of the R-wave of the electrocardiogram (ECG). Thedistance traveled by the pulse wave is measured over the body surfaceand the pulse wave velocity is then calculated as distance/time(O'Rourke et al., 2002), (Wang et al., 2008).

Arterial pulse waves can be detected using pressure-sensitivetransducers or sensors (piezoresistive, piezoelectric, capacitive),Doppler ultrasound, based on the principle that the pressure pulse andthe flow pulse propagate at the same velocity, or applanation tonometry,where the pressure within a small micromanometer flattened against theartery equates to the pressure within the artery (O'Rourke et al.,2002).

As a tool during therapeutic monitoring, cfPWV can be used to assess theefficacy of pharmaceutical antihypertensive agents in decreasingarterial stiffness (William et al., 2006).

Compared to pressure pulse wave analysis, pulse wave velocity does notrequire secondary (e.g., brachial) blood pressure measurements.Moreover, pulse wave velocity has been reported to provide usefulclinical indices of cardiovascular disorders, particularly ofhypertension, in people over 55 years of age.

Aspects of the present disclosure recognize that reliable and continuousassessment of central hemodynamic properties such as arterial stiffnessprovides important input and guidance for the prognostic, diagnostic aswell as therapeutic approaches to cardiovascular disease and for theoverall management of cardiovascular risk. Functional and structuralchanges (e.g., remodeling) in the arterial vasculature with gradualstiffening of the arteries lead to a rise in blood pressure; bloodpressure has become a major risk factor for cardiovascular disease.Arterial stiffness is also an independent marker of cardiovascular risk,even when blood pressure is in normotensive ranges.

In addition to clinical measurements, reliable and easy-to-carry-outhome monitoring of an individual's arterial stiffness and other centralhemodynamic properties could provide useful longitudinal trending ofdata at monitoring frequencies much higher than provided by (relativelyinfrequent) clinical visits and would facilitate both therapeuticintervention and cardiovascular risk management.

Various embodiments of the present disclosure are directed towardsystems and methods for assessing an individual's cardiovascular risk bydetermining the individual's arterial stiffness/elasticity through pulsewave velocity measurements using noninvasive ballistocardiographic andphotoplethysmographic methods. Certain aspects of the present disclosurecan be particularly conducive to facilitating monitoring at home and/orin the clinical setting.

Aspects of the present disclosure recognize that the force generated bythe blood flow interactions with the aortic pressure is tied to theorigins of a BCG signal. This force, the Central Aortic Force (CAF), hasbeen found to be similar in amplitude to the BCG, as shown in FIG. 5.CAF can be determined by:

${CAF}_{y} \equiv {\left\lbrack {\int_{SA\_ aorta}^{\;}{{\overset{\rightarrow}{t}}^{s}\ d\; S}} \right\rbrack \cdot {\overset{\rightarrow}{n}}_{y}}$

The free body diagram of the blood vessel depicts the forces present atthe vessel wall boundary due to fluid-solid interactions. Blood flowexerts forces on the wall with components of pressure (p) and the wallshear stress (τ). By Newton's Third Law of Motion, forces act in pairs;the fluid (t_(f)) is the action force and the elastodynamic response ofthe vessel wall (t_(s)) provides the reactive force, over a smallsurface area (dS). The vessel wall geometry of the aorta with itssemi-circular arch (FIG. 5) provides a three-dimensional system that theforce-pairs to react within. Simulation results suggest that aorticpressure (p) is the main contributor to the CAF (on the order of a fewNewtons). To illustrate the role of the aorta in the production of theBCG forces, simulations of segments of the aorta (FIG. 5) reveal thatthe semi-circular portion aortic arch is a significant, if not aprimary, contributing region to the central pressure-induced forces. Theestablishment of a physiological relationship between the BCG and itsspatial source location in the body supports the use of BCG features(e.g., the I-wave) as a reference for the start of the pressure pulse ina pulse wave velocity calculation, and a valid indication/corollary tothe carotid pulse.

For further details on estimating and detecting central aortic forcesusing BCG reference can be made to Appendix 2 of the underlyingprovisional application 61/475,887 (Estimation of central aortic forcesin the ballistocardiogram under rest and exercise conditions), which isfully incorporated herein by reference along with the references citedtherein.

Embodiments of the present disclosure are directed toward utilizingballistocardiographic (BCG) measurements to acquire hemodynamic timepoints representative of aortic pulse pressure during early systoleinstead of carotid pulse measurements. For further details on BCGmeasurements, reference can be made to U.S. Application US 2010/0094147,filed on Oct. 14, 2009 (U.S. Pat. No. 8,870,780), which is fullyincorporated herein by reference. Accordingly, aspects of the presentdisclosure recognize that BCG measurements can be used in place of (orin conjunction with) tasks often carried out by a skilled technician,such as palpating and locating the carotid pulse.

In addition to ballistocardiographic (BCG) measurements, embodiments ofthe present disclosure are directed toward the use ofphotoplethysmographic (PPG) measurements. The BCG signal results fromthe systolic ejection of blood into the aorta and the start of thedistal PPG signal (e.g., sharp systolic upstroke) begins after thepressure pulse wave travels down the arterial tree to the foot. The Iand J waves of the BCG occur in systole after the pre-ejection period(PEP) has ended, and the BCG waves are mechanically related to bloodflow-induced pressurization of the heart and aorta. Since the BCG wavesoccur in early systole, these BCG wave(s) can be utilized as the firsttime point in the PTT determination (T1), and the foot PPG serves as thesecond timepoint (T2), as illustrated in FIGS. 1A and 1B. The measureddistance between the heart/aortic arch down to the foot can then be usedas a scaling factor to determine velocity (e.g.,velocity=distance/time).

Embodiments of the present disclosure are directed toward the use ofphotoplethysmography (PPG), which is an optical measurement of thevolumetric change of an artery or organ (Allen, 2007). PPG can be usedto measure the pressure waveform of an artery or to quantify oxygensaturation in blood (pulse oximetry). A light source, e.g., an LED, anda photodetector are used to measure the dilation of a blood vessel as aresult of the pressure pulse distending the vessel with sensors beingplaced on the fingertips, forehead, toes or ears. The wavelength oflight of the emitting source is specified to have high absorbancesensitivity in blood (e.g., light absorbance in the 600-900 nm range inblood is sensitive to hemoglobin content in the optical path of the PPGsensor). The PPG sensor can be a reflectance or transmission typearrangement and is placed over a blood vessel such as a conduit arteryor the microcirculation of the small arteries in the fingers, toes, andears. As the blood vessel is pressurized, its diameter increases andthereby the amount of light absorbing material (e.g., blood) in theoptical path increases, causing a decrease in signal at thephotodetector and vice versa when the pressure decreases. The shape ofthe optical signal from the resulting pulse wave is highly correlated inshape and timing to one obtained using a pressure sensor.

Certain embodiments of the present disclosure can be useful forobtaining an accurate estimate of pulse wave velocity (PWV) by averagingover multiple beats together, which can improve the likelihood ofobtaining the true pulse wave timing. For instance, pulse wave velocitycan be determined by using two signals; the ballistocardiogram (BCG) andphotoplethysmogram (PPG), each of which produces a signal containingmultiple heartbeats. Averaging can be used to find the best earlysystolic fiducial timing (typically the I-wave) from the BCG and thebest timing at the start of the PPG signal obtained at the toe. Forinstance, averaging can be applied to timings extracted from individualbeats from a recording or from the ensemble-averaged waveform. Aseparate signal, providing timing information of the heart beat (e.g.,electrocardiogram), may or may not be used to provide reference timingfor ensemble averaging.

Aspects of the present disclosure, can use ballistocardiography (BCG) inconnection with various other methods, such as those used with carotidapplanation, to obtain time points representing the aortic pulse.

Aspects of the present disclosure are directed toward measuring, at asingle location (e.g., the feet, using a modified bathroom scale),multiple signals that each have their origin at two different locationsin the body. For instance, one signal can originate at the aortic archfor the ballistocardiogram, and one signal can originate from below theknee, such as at the lower leg or at the feet (e.g., for a toe PPG).

This aspect can facilitate the measurement of the relative timings ofthese two signals (e.g., to compute pulse wave velocity), because, forexample, there is no need to accurately place highly-sensitive probes atmultiple locations on the body. Such aspects can also be useful forimproved reproducibility of pulse wave velocity measurements, e.g., dueto the ease of the measurement setup procedure.

Aspects of the present disclosure relate to the integration of these twomeasurements into a single device, such as a modified bathroom scale.While a subject stands on the scale, the BCG and foot PPG aresimultaneously recorded. The two signals are recorded at a single point(the feet) that represents two different spatial locations and temporaltimings within the body. The BCG recorded at the feet containsinformation related to the aortic pressure pulse and its timing. The PPGrecords local pulsations within the optical path of the emitter anddetector (e.g., the foot) to represent the arriving pressure wave. Thisconfiguration simplifies the measurement compared to conventionalapplanation methods, as well as methods that rely on sensor placement atdifferent regions of the body to obtain T1 and T2 timepoints.

Embodiments of the present disclosure also allow for the measurements tobe taken from other locations. For instance, the PPG could be takenusing measurements from a subjects hands and/or the BCG could be takenfrom a subject that is sitting on a chair with a pressure sensor.

In one embodiment of the present disclosure, the BCG capture device alsooperates as a weighing scale, such as a bathroom scale that is alsocapable (e.g., modified) for capturing signals from a user. In thisembodiment, the pulse wave velocity (PWV) is estimated using a bathroomscale (see FIG. 1A) with PPG sensors integrated in the scale to acquiredata. The bathroom scale is configured to measure the ballistocardiogram(BCG) and the photoplethysmograph (PPG), both from the feet. This can beparticularly useful for providing consistency in measuring the timeinterval between the BCG and the foot PPG (longer path), which canimprove the accuracy of the velocity estimate. For example, sincevelocity is equal to distance divided by time, a one centimetermeasurement error of the arterial length would manifest in a largererror in the velocity estimate of the carotid to femoral path, versusthe heart to the foot, since the shorter measurement has highersensitivity to measurement error.

Consistent with various embodiments of the present disclosure, a BCGdevice, such as a modified bathroom scale, includes ECG electrodes. TheECG electrodes provide a separate timing reference for the BCG and canalso do the same for the PPG. Such electrodes can be integrated into ahandlebar (wired or wireless) for convenience.

According to other embodiments of the present disclosure, a systemincludes an additional finger PPG sensor to provide information aboutthe relative peripheral pulse wave velocities (velocity in the musculararteries of the legs) and central pulse wave velocities (velocity in theaorta and descending aorta). Using the BCG timing as the start of thepulse wave, the timing of the finger pulse wave relates predominantly tothe velocity through the peripheral arteries (arm). The foot PPG, on theother hand, reflects the propagation through the central (descending)aorta and the peripheral limb (leg). Measurements of both finger andfoot allows the separation of both velocities, either directly (simpleproportionality) or through the use of global or patient-specificmodels. The ability to estimate both the velocity in the central aortaand the velocity in the peripheral arteries can be used to morespecifically assess changes in vascular stiffness in the aorta as wellas to evaluate the efficacy of anti-hypertension drugs working onvascular tone (e.g., ACE inhibitors, angiotensin II receptor blockers).

Consistent with the embodiments discussed herein, the T1 timepoint canbe provided by the BCG measure [“BCG T1”] and corresponds to theproximal, or T1 carotid timepoint, while the T2 timepoint can beprovided by the leg-to-leg impedance cardiogram (ICG) [“ICG-femoral T2”]and corresponds to the T2 distal arterial timepoint. The BCG T1 andICG-femoral T2 timepoints can thereby be used to calculate aorticvascular stiffness. This system may also measure the PPG-toe signal toobtain an additional timepoint of the distal artery [“PPG-toe T2”described earlier] and measurements of both femoral and foot allows theseparation of velocities between the aorta and legs. The ability toestimate both the velocity in the central aorta and the velocity in theperipheral arteries can be used to more specifically assess changes invascular stiffness in the aorta as well as to evaluate the efficacy ofanti-hypertension drugs working on vascular tone (e.g., ACE inhibitors,angiotensin II receptor blockers).

Consistent with the various embodiments of the present disclosure, theseparate velocities or pulse arrival times from the peripheral arteries(arms, leg) and central (descending) aorta can be used to quantify thepressure difference between the brachial artery and aorta (commonlyreferred to as pressure amplification). Using the BCG timing as thestart of the pulse wave, the peripheral and central vascular stiffness'sare measured and an arterial pressure mismatch term is determined. Thepressure amplification term is used in conjunction with a brachial bloodpressure measurement, to determine the central blood pressure. Theability to estimate both vascular stiffness and central blood pressureimproves the ability to identify cardiovascular risk for the managementof hypertension and arterial aging.

In another embodiment of the present disclosure, multiple PPG sensorsare integrated in the modified bathroom scale to measure pressure pulsesat both feet. This multiple PPG sensor arrangement can be particularlyuseful for a number of different applications. For instance, multiplesensors can be used to provide a means to diagnose differentialperipheral arterial disease in the legs (e.g., occlusion, sclerosis orstenosis), to provide a more robust measurement of the pulse arrivaltime by averaging timings at both feet, or to improve robustness throughredundancy.

In other embodiments of the present disclosure, the PPG sensors areconfigured to make additional oxygen saturation measurements possible.

Consistent with embodiments of the present disclosure, the PPG and BCGtimings are derived from a subset of beats taken from the wholerecording. This subset can be selected based on noise metrics (such assignal-to-noise-ratio, using a fixed or patient-specific threshold), orusing an embedded noise reference in the scale (e.g., Wiard et al.,2010) to negate the need for ensemble averaging based noise metrics. Aquality metric, indicative of the confidence in the PWV valuecalculated, can also be derived from these noise or motion metrics.

Embodiments of the present disclosure relate to a system that providesinformation on PWV and pulse wave analysis (PWA) utilizing the BCG andPPG signals. The analysis of the PPG waveform shape provides informationon the wave reflection return to the heart, with respect to the timingin the cardiac cycle, while the standing/upright PWV is determined. Theability to provide simultaneous information on PWV and wave reflectiontimings can be used to evaluate the efficacy of antihypertensive drugsworking on the arteriole bed where PWV may not change significantly, yetblood pressure may change due to the degree of reflection in capillarybeds.

The following discussion first addresses various embodiments of BCG(ballistocardiogram) systems and methods and then addresses embodimentsrelating to (among other things), using a motion sensor and filter,measuring of arterial aging and measuring of multiple signals at asingle location. The order of the discussion does not limit the importof the discussed subject matter, nor does it limit the ability tocombine and supplement various embodiments discussed herein.

In another example embodiment, a BCG (ballistocardiogram) systemincludes a BCG capture device including a heart-characteristic sensorthat captures, from a user, a BCG signal indicative of at least one ofphysical movement and mechanical output of the user's heart. A secondarysensor detects a secondary characteristic relating to the BCG signal,and provides an output characterizing the detected indication. Forexample, the secondary sensor may detect characteristics of a userand/or of the user's environment to provide an indication of one or moreof noise present in the BCG signal and a physiologic characteristic ofthe user. A processor circuit uses the secondary sensor output toprocess the captured BCG signal and to generate an output BCG signalindicative of a condition of the user's heart and ascending aorta (e.g.aortic arch).

In some implementations, the BCG capture device includes a weighingscale, and the secondary sensor includes an electrocardiogram (ECG)sensor that detects an ECG signal from the user, or aphotoplethysmograph sensor that detects blood flow pulsations of theuser. This detected signal is used to process a signal obtained via theBCG capture device.

In another implementation, the secondary sensor includes an ECG sensorthat detects an ECG signal from the user that is indicative of, orotherwise useful for determining, characteristics of the user andrelated BCG signal capture. The processor circuit uses an algorithm toprocess the captured BCG signal and to generate the output BCG signalusing the detected ECG signal as an input to the algorithm to processthe BCG signal. In certain applications, the processor circuit generatesan output BCG signal based upon an ensemble-average of the detected BCGsignal generated via the detected ECG signal. This averaging can be bothstatic—providing a single ensemble-averaged BCG beat—or dynamic, as insynchronous moving averaging or exponentially-weighted triggeredaveraging.

In some implementations, data is detected for both BCG- and ECG-basedanalysis using a strip-type sensor or a handlebar-type sensor that maybe implemented on a scale device as discussed herein (see, e.g., FIG.14B and FIG. 14C, discussed further herein). One or more such sensorsare used to effectively capture a signal from a user that issubsequently processed to generate both BCG and ECG analysis data. Insome implementations, ECG data that is detected and/or generated is usedin the generation of BCG analysis data, such as by filtering a capturedsignal to facilitate the representation of one or more of physicalmovement and mechanical output of the user's heart. For example, BCG andECG (or photoplethysmograph) signals can be adaptively filtered, orprocessed via ECG R-wave (or photoplethysmograph timing) triggeredensemble averaging or triggered moving averaging, to improve thesignal-to-noise ratio and the consistency of BCG recordings.

In some embodiments, a strip-type or handlebar-type sensor as discussedabove includes a two-electrode ECG circuit configured for contacting thehands of a user. In some implementations, the two-electrode ECG circuituses active current feedback to one electrode to reduce amplifiersaturation problems, rendering higher signal quality on the ECGrecordings. Detected ECG characteristics can then be used for adaptivelyfiltering, ensemble averaging, or otherwise processing the BCG signalmeasured from the force sensor in the scale, to improve the signalquality of the BCG.

In some implementations, the ECG or photoplethysmograph (or otherreference signal) is adaptively filtered to estimate the BCG to mitigaterequirements or needs for detecting peaks or heartbeat segmentation, oruse of an R-wave detector (e.g., for ensemble averaging or triggeredmoving averaging). In some implementations, an ECG orphotoplethysmograph signal is fed directly into an adaptive filter, withthe raw BCG signal as the desired response; the output of this filter,to form a best least-squares estimate of the signal without any need forECG or photoplethysmograph peak detection. In some implementations, aleast-mean squares algorithm is used to adapt weights of the adaptivefilter. The convergence rate can be chosen to be slow, allowing thefilter to converge to the best solution for the user of the device.

A specific implementation involves the use of a scale having customelectronic circuitry for acquiring and processing the BCG signal. Usersof the scale position themselves on the scale. The weight is measuredand recorded as a function of time. The sensitivity of the measurementis sufficient in both weight and sample speed so that thegenerated/recorded signal contains the desired BCG signal. Forrelatively small BCG signals (compared to a number of other sources offorce variances such as respiration, user movement, building vibrationsand/or electrical noise), aspects of the present disclosure are directedto detecting the BCG signal, relative to one or more of the aforesaidsources. In some implementations, the amplitude of the BCG signal iscorrected based upon the weight of a user, based on kinetic energytransfer. A variety of scales, commercial or custom can be modified toacquire a BCG signal, which can be implemented in connection withvarious example embodiments. For instance, the Omron HBF-500 BodyComposition Monitor/Scale available from Omron Healthcare Inc., ofBannockburn, Ill. can be implemented in connection with one or moreexample embodiments.

Another example embodiment is directed to a BCG system as describedabove, having a bodyweight sensing scale with an ECG and/orphotoplethysmograph sensor integrated into the scale platform,detachable unit, or separate unit connected to the scale. In someimplementations, the BCG capture device is integrated with thebodyweight sensing scale, and the secondary sensor is integrated withhandlebar electrodes. The electrodes and secondary sensor detect atleast one of an electrocardiogram (ECG) or photoplethysmographycharacteristic of the user. The processor circuit generates output BCGsignals over time to provide an indication of at least one of cardiacoutput and stroke volume for determining a treatment need for the user,such as for titration of care for the user (e.g., for the adjustment ofmedicine dosage (with physician consultation) or signaling the need fora clinical visit).

In some implementations, the BCG capture device is integrated with thebodyweight sensing scale, and the secondary sensor is integrated in atleast one of the scale platform, a detachable module, or a separatemodule connected to the scale via hardwire or wireless link. Thesecondary sensor detects a photoplethysmography characteristic of theuser. Consistent with certain embodiments of the present disclosure, adetachable PPG can be used on an ankle. This can be particularly usefulwhen a user has poor signal from the feet (e.g. micro vascular diseasefrom diabetes mellitus). Accordingly, the ankle can provide an alternatesite for the T2 measurement.

Turning now to the figures, the user depicted in FIGS. 1A and 1B ispositioned on the scale-based system. The scale includes a force/weightsensor FIG. 14A. This sensor is configured to detect weight variationsthat are converted to an electrical signal FIG. 3 that is sent toprocessing arrangement, and can be further used to provide the weight ofthe user, such as that provided by a traditional scale.

Secondary input(s), FIG. 14A provide information in addition to strictforce sensing. These inputs can include, for example, signals providedby heart-beat sensors, foot-to-foot impedance cardiogram sensors, usermovement sensors and the like, which may further be incorporated intothe system. In some implementations, impedance plethysmography orphoto-plethysmography sensors can be used to improve signal processing.

Still other implementations are directed to addressing motion artifacts,such as by using a secondary non-contact displacement sensor to measurecorrelated cardiac related information and uncorrelated body motionnoise and remove motion artifacts, FIG. 14C. One such implementationinvolves using a displacement transducer such as an optical oracoustical emitter/detector sensor, to measure absolute or relativechanges in body motion to improve the cardiac signal. Another approachto removing motion artifacts involves using multichannel sampling onindividual strain gages, or by switching a bridge circuit to capturedifferent motion axes.

The processing arrangement is configured to use the secondary input(s)and various filtering algorithms to remove extraneous noise orinterference on the signal from sensor. The results of thisprocessing/filtering can be sent to an output, such as an LCD display orlocal memory. This information can be presented in a recordable form,such as for recording by the patient using the system, or for uploadingfor access by a doctor at a remote location. In some instances, theoutput includes a network interface type device that provides an outputto a network (e.g., Ethernet or wireless) connected to one or morestorage devices that receive output data from scale. In other instances,the output includes one or more of a Universal Serial Bus (USB)connection, a point-to-point (non-network) wireless link, removablememory card device, contactless card device, or a relatively simpleindicator that shows when abnormal cardiac function has been detected(e.g., warning the patient to contact a doctor).

According to one implementation, an ECG signal (single or multiple lead)is recorded simultaneously with weight-related detection (e.g., weightvariations as discussed above) and used as a secondary input conditiontogether with the detected weight-related condition. The signals fromthese recordings are combined using adaptive filtering, such as byadaptively filtering a secondary signal to determine the bestleast-squares estimate of the BCG signal from a raw weight measurementwaveform. This approach leverages the fact that the ECG and BCG signalsare correlated in time, while the noise components in these waveformsare statistically independent.

In another implementation FIG. 14B, heart beat (e.g., ECG orphotoplethysmogram)-triggered ensemble averaging is used to enhance thequality and consistency of the BCG signal. Such a technique leveragesoff the ability to easily detect heart contraction using any of a numberof different techniques. Detected heart contractions are then used toselect relevant portions of the detected BCG measurement to use inensemble averaging. For example, ensemble averaging may be used tomitigate noise in the BCG signal.

In various implementations, an adaptive filtering approach using aleast-mean-squares algorithm is used to remove noise from the BCG signalwith the ECG signal as a reference. BCG signals are ensemble-averagedusing the ECG R-wave as the trigger. This ensemble averaging can be bothstatic (one average for the entire data set) and dynamic (synchronousmoving average). Additionally, respiration signal can be used as areference for adaptive noise cancellation of respiration from the BCG.In certain applications, the system in FIG. 14A is configured forself-calibration to eliminate instrumentation resonance, to decouplemechanical filtering of the signal by the scale other device used tocapture the BCG signal.

FIG. 14A shows a block diagram of a system for detecting cardiacfunction involving both ECG and BCG detection, consistent with anotherexample embodiment of the present disclosure. The system can be used ina manner similar to that as described above in connection with FIG. 1,and further with the above examples using both ECG and BCG, fordetecting conditions of a user's heart. A scale-type BCG sensor deviceincludes an ECG-type hand-held sensor that detects ECG characteristicsthat are used in connection with BCG characteristics detected at thescale-type device. An output from the BCG sensor device is passed to aprocessor that processes the output and detected ECG and BCGcharacteristics therein, to determine a heart-based condition of a user.In various implementations, one or more additional sensors, representedat block, are also coupled to the processor, which uses the inputs aspart of the determination of the heart-based condition (e.g., such as avibration sensor that is used to remove noise in one or both of a BCG-and ECG-based signals).

In connection with various embodiments, acquired signals as describedherein are used in deriving/monitoring various different types ofinformation including, but not limited to, heart rate, the force ofejection of blood from heart (which can be correlated to cardiacoutput), time delay from electrical depolarization to mechanicalcontraction of the ventricles, relationship between electrical andmechanical activity in the heart (relating to excitation-contractioncoupling), pressurization of the ascending aorta, predicting futurecardiac health trends and/or non-invasive blood flow and pressuremeasurements.

Various aspects of the present disclosure are directed to use in a homeor other location where it may not be practical to have a trainedtechnician or physician available. In one implementation, simultaneousBCG and ECG recordings from a commercial bathroom scale or chair areused to facilitate home monitoring of cardiovascular health in a compactand inexpensive platform for reliable BCG acquisition. BCG measurementscan be implemented for chronic management of hypertension patients athome.

FIG. 3 shows a circuit for acquiring BCG signals from a commercialweighing scale, consistent with another example embodiment of thepresent disclosure. The circuit is amenable to BCG acquisition from aweighing scale. The strain gauges within a commercial scale, such as anOmron HBF-500 scale, are arranged in a Wheatstone bridge configuration.The bridge is excited by a dc voltage of +/−9V, and the differentialvoltage across the bridge is amplified by an instrumentation amplifier(the LT1167) which is dc-blocked using integrative feedback (LT1014C).The output from this dc-blocked instrumentation amplifier stage is thenband-pass filtered and further amplified. The circuit gain is 90 dB,with a bandwidth sufficient for high-resolution BCG acquisition.

The specific circuit depicted by FIG. 3 is exemplary of a number ofdifferent implementations that can be used to provide similarfunctionality. As with other aspects of the present disclosure, thevarious functionalities can be implemented using combinations of generalpurpose computers configured by specialized software, programmable logicdevices, discrete circuits/logic and combinations thereof.

The following description references a number of Appendices, inconnection with various example embodiments. Each of these Appendices isfully incorporated herein by reference.

Referring to Appendix B (IEEE EMBS 2009 Conference Paper), attached tothe U.S. patent application Ser. No. 12/579,264 filed on Oct. 14, 2009(U.S. Pat. No. 8,870,780), aspects of the present disclosure aredirected to BCG signal estimation and to Cardiac ContractilityAssessment Using BCG, as applicable to one or more of the followingexemplary embodiments:

-   -   1. A BCG “pulse response” is defined as a BCG characteristic for        each subject that may persist for a longer time period than a        single heartbeat. This pulse response may, for example, include        a mechanical response of the arteries and body to the pulse of        blood ejected by the heart; these mechanical structures may        continue oscillating long after this initial pulse of blood,        causing the average BCG response to be longer in duration than a        single heartbeat. In this context, the pulse response is used in        characterizing aspects of the subject from which the BCG        response is captured.    -   2. ECG R-wave timing is used as a timing reference to compute a        “short-window” ensemble average BCG. This short-window average        is then used to estimate the amplitude of each BCG heartbeat for        the entire recording. BCG heartbeats are then re-segmented using        an ECG timing reference with a “long-window” process. These        long-window beats are then averaged after subtracting        surrounding beats from each BCG heartbeat, yielding an        interference-cancelled long-window BCG pulse response.    -   3. The interval between the ECG R-wave and the BCG J-wave (R-J        interval) is inversely correlated to changes in cardiac        contractility. The R-J interval is used to characterize the        contractility, in which a higher contractility leads to a lower        R-J interval, and vice versa.    -   4. The signal-to-noise ratio (SNR) of each heartbeat is detected        using normalized ensemble correlation and, in some        implementations, R-J intervals are disregarded for heartbeats        with relatively lower SNR.    -   5. The time interval between the pre-ejection period (PEP) and        the R-J interval for each subject is used to characterize        arterial compliance. Less compliant arteries are detected        identified via shorter propagation delay between the ejection of        blood at the heart and a mechanical wave detected at the feet of        a subject (e.g., as akin to a rigid pipe propagating an acoustic        wave faster than a compliant, soft pipe).

Referring to Appendix D (Robust BCG Acquisition for Home Monitoring),attached to the U.S. patent application Ser. No. 12/579,264 filed onOct. 14, 2009(U.S. Pat. No. 8,870,780), aspects of the presentdisclosure are directed to BCG acquisition at home, as applicable to oneor more of the following exemplary embodiments:

-   -   1. A BCG signal is used in conjunction with bodyweight        measurements on a scale that is also used for monitoring the        health of heart failure patients at home. The BCG signal is used        to provide a measure of changes in perfusion by estimating        changes in cardiac output; bodyweight measurements can (e.g.,        simultaneously) provide an estimate of congestion by evaluating        weight change due to fluid retention. Both of these measurements        can be combined to provide a desirable assessment of a person's        cardiac health, since subjects can have congestion without        perfusion or perfusion without congestion.    -   2. Photoplethysmograph and ECG signals are used for averaging or        filtering a BCG signal, such as obtained herein.    -   3. Beat-by-beat BCG amplitude (J-wave) is used to characterize        the stroke volume for a particular beat to which the wave        applies.    -   4. The ECG R-wave timing is used as a timing reference to        compute a “short-window” ensemble average BCG. This short-window        average is then used to estimate the amplitude of each BCG        heartbeat for the entire recording. BCG heartbeats are then        re-segmented using the ECG timing reference, with a        “long-window” process. These long-window beats are then averaged        after subtracting surrounding beats from each BCG heartbeat,        yielding an interference cancelled long-window BCG pulse        response.

Referring to Appendix F (Valsalva Paper), of the U.S. patent applicationSer. No. 12/579,264 filed on Oct. 14, 2009 (U.S. Pat. No. 8,870,780),aspects of the present disclosure are directed to using a Valsalvamaneuver, as applicable to one or more of the following exemplaryembodiments:

-   -   1. BCG measurements are taken during a Valsalva maneuver to        elicit various expected reflexes from the cardiovascular system.        A response to the Valsalva maneuver can be used to diagnose        diseases or conditions. For example, a patient with prior        myocardial infarction may not see increased BCG amplitude after        releasing the strain, whereas a healthy subject certainly does.        BCG amplitude can thus be monitored and used to identify such        conditions.    -   2. For cases when a simultaneous ECG is unavailable, a BCG        J-wave rise time is used as an indication of changes in cardiac        contractility.    -   3. A frequency domain analysis of a BCG signal is performed and        used to provide indications of the state of cardiac        contractility, by examining the ratio of high-frequency to        low-frequency power in the power spectral density of the BCG.

Referring to Appendix G (Two Electrode Biosignal Amplifier for ECGMeasurement), attached to the U.S. patent application Ser. No.12/579,264 filed on Oct. 14, 2009 (U.S. Pat. No. 8,870,780), aspects ofthe present disclosure are directed to measuring an ECG, as applicableto one or more of the following exemplary embodiments:

An ECG is measured in “current-mode” using a transimpedance amplifierfront-end, which leads to a low differential input impedance, andmitigates microphonic cable noise that can occur due to the movement ofthe cables during acquisition.

-   -   1. Current feedback is delivered to an input terminal using a        non-inverting integrator sensing low-frequency variations in an        output signal, and used to stabilize common-mode voltage at the        input and prevent amplifier saturation and other undesirable,        commonly-encountered problems in two-electrode (as opposed to        typical three-electrode) ECG recordings.    -   2. A micro-power op-amp is used with the bandwidth boosted by a        composite amplifier design, facilitating desirable current        consumption (e.g., about 3.9 micro-Amps), such that a battery        could operate the device continuously for years.    -   3. A lead-capacitor is used in the first stage of a composite        amplifier to set a second-order sharper roll-off in the overall        closed-loop response of the circuit, facilitating a greater        degree of attenuation at the Nyquist frequency for sampling in        analog-to-digital conversion of the signal.    -   4. A resistor is placed at a non-inverting terminal of an input        op-amp, connecting this terminal to ground, matching the        common-mode input impedances at the two input terminals. This        approach can be used, for example, to facilitate an optimized        (e.g., desirable) common-mode rejection ratio.    -   5. An ECG circuit is embedded in the handlebar electrodes of a        commercial weighing scale to provide an R-wave timing reference        for BCG signal averaging.    -   6. An ECG circuit is used for acquiring other biomedical        signals, such as electroencephalogram (EEG) signals from the        scalp.

Aspects of the present disclosure relate to a noise signal referencethat can be used to systematically identify motion while standing on aBCG scale. In some situations, motion of a patient leads to anunacceptable number of noisy segments in the BCG. The BCG force signallevel is on the order of a few Newtons in magnitude. Body movement caneasily introduce noise artifacts of similar magnitude and ordersgreater. Noise on the order of the BCG signal level can be difficult todetect from the BCG signal alone. For instance, a method can use asecondary set of strain gauges and an analog amplifier to measure bodymotion while standing on the scale.

Consistent with embodiments of the present disclosure, a motion signalcan be obtained from a BCG scale using secondary strain gauge sensorsthat measure weight distribution changes. Consistent with otherembodiments of the present disclosure, a motion signal can be obtainedfrom a BCG scale using sensors to measure the weight of the patientwhile also measuring weight distribution changes.

The motion of standing subjects can be modeled as an inverted pendulum,where body motion is highly correlated to anterior-posterior weightdistribution changes and can be used as a noise reference technique forstanding BCG measurements.

Consistent with a particular embodiment of the present disclosure, fourload cells can be used to provide simultaneous BCG and motionmeasurements. Each load cell includes of a metallic strain gauge (e.g.,Tanita strain gauge) that is affixed to a mechanical cantilever beam.Additional strain gauges can also be used (e.g., 350 X Omega metallicSGD-7350-LY13, Omega Engineering Inc., Stamford, Conn.). For instance,the additional strain gauges can be placed on the opposite side of thecantilever from the original strain gauge. Thus, deflections in the beamrepresent tensile strain for the one set of the strain gauges andcompressive strain for the other set of strain gauges.

According to various embodiments of the present disclosure, secondarystrain gauges were added to strain gauges that were specificallyconfigured into a Wheatstone bridge to record the BCG. The sensors canbe chosen according to their size relative to the physical spaceavailable for mounting on the cantilever.

According to embodiments of the present disclosure, the motion-sensingcircuit for the additional strain gauges includes an instrumentationamplifier with a gain of 1,000 and a Sallen-Key low-pass filter (secondorder, 24 Hz cutoff). The additional strain gauges can be wired into ahalf-bridge arrangement to detect anterior-posterior motion, and theoutput can then be recorded simultaneously with the BCG andelectrocardiogram (ECG), at a suitable (e.g., 1 kHz) sampling rate.

FIG. 14C depicts a block diagram of the overall measurement setup,consistent with embodiments of the present disclosure. The depicteddevice upon which the user stands can be specially designed or can be abathroom scale that has been modified to measure the BCG and a signalrepresenting body motion. Human balance can be quantified by measuringthe changes in the center of mass (COM) position in theanterior-posterior plane using force plates. The true COM movement canbe correlated with the changing pressure signal on force plates, whichdemonstrate that the COM and weight shift signals track together indirection and amplitude, with virtually no lag between the two signals.For further details on this correlation, reference can be made to Winteret al., which is fully incorporated herein by reference.

For an experimental setup (discussed in more detail hereafter), amodified bathroom scale was configured to measure the anterior-posteriorCOM weight shift to represent the motion signal.

Aspects of the present disclosure recognize that the system can becharacterized in terms of the overall frequency response of the BCGrecording system. Generally speaking, the data bandwidth is limited bythe circuitry and mechanical bandwidth is limited by the stiffness anddamping of the scale. Calibration can be used to determine the responseof the recording system (e.g., whether the system provides linearity).The mechanical frequency response of the scale and strain gauges can beestimated through a series of impulse response measurements, e.g., withvarying at loads. The bandwidth of the scale platform should besufficient to measure the BCG.

Embodiments of the present disclosure are directed toward amotion-signal-derived noise metric that flags segments of the BCGcorrupted with excessive motion. This embodiment can use a noise indexthat is calculated as follows: first, a baseline recording can be usedto establish a ‘normal’ RMS level for the motion signal. This ‘normal’level can then be used to set a subject-specific threshold, e.g., twicethe ‘normal’ level, above which the BCG trace was considered corruptedby noise. As a result, periods of the BCG signal during which the motionwas greater than the threshold were considered ‘high’ for the noiseindex, and other periods were ‘low’.

Consistent with other embodiments of the present disclosure, anon-subject-specific, fixed, threshold can be set for all recordingswithout the use of a baseline recording. For instance, a fixed thresholdcan be set as the average subject-specific threshold measured for allparticipants. Noisy beats can be removed based on the noise index andthe SNR improvement using both the subject specific.

For further details regarding experimental results and various specificembodiments, reference can be made to Appendix 1 of the underlyingprovisional application 61/475,887 (Automatic detection of motionartifacts in the ballistocardiogram measured on a modified bathroomscale), which is fully incorporated herein by reference. The variousexperimental results, embodiments and discussions of the Appendix 1 arenot meant to be limiting.

The following experimental methods and materials were used in theexamples that are described further below.

Data is acquired over a duration sufficient to obtain multiple beats,usually 5-30 seconds in length. This data is known as a time trace. Atime trace is obtained for the BCG, PPG and electrocardiogram (ECG).

The BCG and PPG signals contain relevant information in the bandwidth ofapproximately 0-20 Hertz, and the time trace contains informationin-and-above this range. Frequency content outside of this range isconsidered to be noise and can be removed (e.g. 60 Hz noise from ACpower sources). The mechanical frequency response of the scale is afunction of its stiffness and coupling to the floor to transduce themechanical actions of the BCG. A digital FIR filter is used to low-passfilter the time trace at 25 Hz leaving just the low frequency content.

It has been discovered that the mechanical stiffness of the scale islinked to the ability to collect the BCG signal between 0-20 Hz. If thescale construction and/or contact with the floor are not sufficientlyrigid then the BCG may be attenuated or distorted, even if the analogand FIR filters are set properly. Also, how well the scale is coupled tothe surface can affect the ability to obtain a BCG. For instance, acarpet can be problematic. Accordingly, aspects of the presentdisclosure recognized that the use of a stiffening plate can beeffective when placed between the scale and the carpet.

The ECG is used as a timing reference signal to identify where tosegment the BCG and PPG time trace into individual beats. The ECG is notas susceptible to noises present in the BCG and PPG and the ECG R-wavetimings are very easy to identify with software algorithms. Once theR-wave timings are located, those timings can be used to segment the BCGand PPG signals into individual beats. Beats are segmented by“windowing” where a fixed frame is drawn around the beat. For example,we can choose a window to be 1-second in length. For each R-wave timingpoint, a 1-second window is placed over the BCG and PPG time traces atthe R-Wave timing point, to “cut” the time trace into individual beats(referred to as ensembles). Shorter or longer windows may be used,depending on how much beat information is required for each ensemble.

An alternate method for beat identification is to identify noisy beatsbased on a reference sensor embedded in the scale to detect abnormalbody motion. The ECG is not required for this method. Beats aresegmented by “reverse windowing” using the foot PPG signal timings toprovide a fixed frame to extract timing features of the BCG. Once thebeats are windowed, noisy beats (BCG and/or PPG) may then be removedfrom the analysis based on the signal level and timings of the bodymotion reference signal that exceeded a pre-determined threshold. Themotion sensor in the scale is configured in a manner to measure signalssuch that it is highly correlated to noise metrics that can be derivedfrom ensemble averaging methods and is validated to be a surrogate noisereference. In this manner, the PWV determination may be obtained from ascale-only embodiment, where standing on the scale will collect all datanecessary to select and exclude beats in the analysis.

To obtain an estimate of a key time point in the BCG or PPG ensemble(e.g. the BCG I-wave), BCG and PPG beats are averaged to produce anEnsemble Average; one for the BCG and one for the PPG.

To extract the I-wave timing from the BCG beats, the first local minimaleft of the J-wave in the BCG is considered. Accurate detection of theJ-wave is achieved by finding the closest local maxima from an expectedJ wave location. This expected location is defined as the location ofthe largest maxima in the ensemble average of all BCG beats.

For the PPG, the foot of the PPG is identified by finding the peak inthe PPG beat, the slope of the rising pressure wave to the left of it,and the zero-slope at the first minimum to the left of the rising slope.The intersection of these two lines represents when the pressure beginsto rise in the PPG waveform. In other embodiments, various other methodsfor extracting the beginning of the pressure rise can be used, such asmethods based on derivative versions of the signal.

To improve accuracy, the feature identification is performed onindividual beats, and then averaged over all beats. Alternatively, thefeature identification is performed on the ensemble-averaged PPG or BCG.

Once both BCG I-wave and PPG foot timings are obtained, their difference(PPG-BCG) is computed to obtain the PTT. The distance between the aortaand the foot is measured. PWV is then calculated as: PWV=(distance)/PTT.

It is noted that neither PWV nor PTT are identical to PAT, which is theR-wave to pressure pulse time, rather than pressure-to-pressure timing.

If a second PPG sensor attached to the finger is used, an estimation ofthe pulse wave velocity along the descending aorta and in peripherallimbs can be proposed. Assuming the distances between the aorta and thefinger (L_(arm)), between the aorta and the pelvis (L_(trunk)) andbetween the pelvis and the foot (L_(leg)) are known, and the pulsetransit times to the finger (PPT_(finger)) and foot (PTT_(foot)) havebeen measured using the methods described above, the followingderivations can be written:

$\begin{matrix}{{{PWV}_{arm} = \frac{L_{arm}}{{PTT}_{Finger}}}\mspace{14mu}} & (1) \\{{PWV}_{leg} = {f_{TF}\left( {PWV}_{arm} \right)}} & (2) \\{{PWV}_{trunk} = \frac{L_{trunk}}{{PTT}_{Foot} - \frac{L_{leg}}{{PWV}_{leg}}}} & (3)\end{matrix}$

The relationship between the pulse wave velocity in the arm and the legis given by the function ƒ_(TF). In a first-order approximation, thesetwo velocities are considered equal (a uniform peripheral velocity), andthe central velocity (PWV_(trunk)) can be rewritten as:

${PWV}_{trunk} = \frac{L_{trunk}}{{PTT}_{Foot} - {\frac{L_{leg}}{L_{arm}}{PTT}_{Finger}}}$That relationship ƒ_(TF) between arm and leg pulse wave velocities isnot limited to identity, and may also be more complex to account forvascular differences between arms and legs, and may take into accountparameters such as average diameter, pulse pressure, or relativecompliance. Such models could either be global, or patient-specific.

The following experimental examples are not intended to limit the scopeof the present disclosure. For instance, the specific values,measurements and observations are not necessarily limiting and wouldgenerally be understood as being capable of modification.

The ballistocardiogram (BCG) is used as the first time point reference(e.g. a surrogate measurement for the carotid pressure), since the BCGhas been related to the peak forces generated by pressure acting on theaortic arch (Wiard et al., 2009). This relationship may also be derivedempirically by measuring the BCG and carotid pulse simultaneously.

FIG. 10 depicts the timing relationships of the BCG to the peripheralPPG signals at the finger and toe. The ECG represents the start of theheart cycle. The BCG begins immediately after cardiac ejection in earlysystole, and distal pressure waves are recorded with the PPG. The delaybetween the start of the BCG and the PPG-toe signal quantifies thepressure pulse wave time.

The timing relationships depicted in FIG. 10 demonstrate that the BCGpulse begins prior to both the finger and foot photoplethysmogram (PPG).In this example, the I-wave of the BCG begins 10 ms and 120 ms prior tothe base of the PPG finger and foot signals, respectively. The J-wave ofthe BCG begins 30 ms and 280 ms prior to the peak of the finger PPG andfoot signals, respectively. The arterial length of the aortic arch tofinger PPG is roughly half the distance of the aortic arch to PPG footsignal, however the finger PPG signal is more than 10 times faster. Thisis believed to be due to the fact that the finger PPG traversed themajor upper branch vessels, while the PPG pulse traveled down acompliant aorta and then through the muscular arteries extending pastthe iliac bifurcation. The compliant aorta has a slower wave speed, thusthe PPG foot pulse arrival time will not be directly proportional to thedifference in the path length traveled, when compared to the finger PPG.However, since the finger PPG reflects predominantly peripheral velocity(velocity in the muscular arteries), it can be used, directly orindirectly, to estimate the specific velocity in the descending aorta.Indeed, the peripheral velocity derived from the finger PPG can be usedto assess how much time has the pulse recorded with the foot PPG spenttraveling in the lower limbs (at a peripheral velocity) versus in thedescending aorta (at a central velocity) as exemplified in FIG. 2. Asnoted above, the relationship between arm and leg pulse wave velocitiescan either be of identity, proportionality, or based on more complexvascular models taking into account parameters such as average diameter,pulse pressure, or relative compliance. Such models could either beglobal, or patient-specific.

A closer examination of time point T1 is shown in FIG. 6. The carotidartery pulse was measured with a reflectance PPG sensor and standing BCGmeasurements were obtained simultaneously and start very close to oneanother (T1 demarked by circles) at the beginning of systolic ejection.As described in Wiard et al. 2009, the BCG has two important features:(1) the BCG force is related almost entirely to the pressure exerted onthe aortic wall, and (2) the generation of the peak BCG force is locatedin the aortic arch. Accordingly, it is believed that the BCG T1 timepoint is related to pressure in the aortic arch which is sufficientlyclose to the carotid artery where the traditional T1 time point isregistered. Consequently, the BCG timing and distance relationship of T1shown in FIG. 5 are considered sufficient to represent the carotidpressure pulse start point.

The BCG-based pulse wave method was verified in a manner where vascularstiffness could be modulated. In this setup, the BCG was recorded on amodified bathroom scale and continuous blood pressure measurements wererecorded using a Portapres ambulatory blood pressure monitor with asubject performing a Valsalva maneuver. The maneuver is divided intothree intervals: (1) rest, (2) strain, and (3) release. The rest phasedepicts normal blood pressure. During strain, the subject holds theirbreath which compresses the return vein to the heart and the ejection ofblood from the heart that manifests as a decrease in systolic bloodpressure. At this lower pressure strain phase, the arteries are lessstiff and there is a decrease in pulse wave velocity. During release,flow is restored to the heart, ventricular fill is increased and theheart contracts with enhanced force resulting in high systolic pressuresfor a short period of time that quickly return to baseline. During highsystolic pressure, the arterial tree is stiffer and pulse wave velocityis increased. As shown in FIG. 15, the bathroom-scale PWV (bottom)measurement trends with the continuous blood pressure acquisition (top).In this example a Valsalva maneuver was performed. The maximumcross-correlation between these time traces is 0.73.

For the management of hypertension, embodiments of the presentdisclosure provide a platform to monitor and trend blood pressurechange, as illustrated in FIG. 15. Arterial stiffness is related to theelastic modulus of the vessel and pressure in a vessel, and may bedescribed under Laplace's Law:T=P·Rwhere the wall tension (T) is related to pressure (P) and the vesselradius (R) and the response of the vessel wall will depend on itsstiffness. Therefore, PWV may be used as a correlative parameter forblood pressure change based on the BCG and foot PPG signals and thecorrelation will benefit in terms of its accuracy due to the inherentrepeatability in the stiffness measurement, as previously described.Additionally, the ability to tease apart central versus peripheralvelocities may further improve the accuracy of the method as shown inFIG. 2, since central velocity might be less affected by vascular tonecompared to velocities in the limbs.

Suitability for in-home monitoring use. For determining an individual'sarterial stiffness/elasticity, the individual stands on the modifiedbathroom scale, while the BCG, ICG, and PPG are simultaneously acquiredat the feet to determine central hemodynamic properties such as arterialstiffness/elasticity. Although the BCG as the first signal occurs at theaortic arch, there is a negligible transmission delay when measured atthe feet. So, the BCG measured at the feet can serve as a timingreference similar to the carotid artery pulse in the neck, thuseliminating the need for the carotid measurement for determiningvascular stiffness. The additional use of the ECG, and a second fingerPPG in some embodiments, does not alter the user-friendliness andconvenience of the overall system, as both sensors can be easilyintegrated into a simple handlebar that the individual holds during themeasurement.

The PPG is an optical sensor and records a signal of vessel dilation dueto local pulsations in the foot, as shown in FIGS. 1A and 1B. Anaccurate pressure pulse waveform can be obtained from the bathroomscale, while the subject is standing on it. Since both BCG and PPGmeasurements for the determination of arterial stiffness/elasticity areobtained simultaneously at the feet while the individual is standing onthe modified bathroom scale, there is no need to locate or palpatearteries or apply probes and, thus, no medical supervision and/orassistance by a skilled technician is needed.

The scale-based system described herein integrates several relevantsignals related to the circulatory function and the data collected andanalyzed can be displayed to the user via a display included with thesystem as a standalone device, or networked/integrated as a device partof a home health network that communicates data to the patient's careproviders.

Relevant arterial path mapped. The path from the heart to the feet isthe longest section of the arterial tree and coincides with the pathaltered with antihypertensive medications. In general, antihypertensiveslower blood pressure by reducing the stiffness of the muscular arteriesin the legs, which slows the pressure pulse wave speed and itssubsequent reflection back to the heart. As noted above, the ability toestimate velocities along both the descending aorta and the legs,although not necessary, further augment the monitoring capability of thesystem.

Suitability for arterial stiffness measurements. The trending ability ofthe standing arterial stiffness measurement, consistent with embodimentsof the present disclosure, is comparable with methods using the timingof the carotid artery as a T1 time point. As shown in FIG. 8, alongitudinal study was conducted over a four month period for thesimultaneous acquisition of the BCG I-wave timing and the carotid arterytiming for an individual. For each 30-second data collection, the timingrelative to the ECG R-wave demonstrates that the carotid and BCG havesimilar: average timing, and similar measurement variability. For theDay 1 measurement, the individual in this experiment had administered abeta blocker, and the timings were measured pre and post administrationand there is a significant change in the average timings of the carotidartery and BCG I-wave Pulse Arrival Timing (PAT). The longitudinal PulseTransit Time (PTT=T2−T1) was then determined using both BCG and carotidtimings for T1 and shown to be similar, as shown in FIG. 9, where the T2timing was acquired at the foot using embodiments consistent with thepresent disclosure. FIG. 12 depicts the standing pulse wave velocityversus the age of the individual which increases over time and is aconsistent for arterial stiffening. FIG. 16A is a graph of the centralsystolic pressure obtained using a SphygmoCor arterial tonometer for agroup of individuals. FIG. 16B is a graph of the standing pulse wavevelocity consistent with embodiments of the present disclosure versusthe central systolic blood pressure. The central systolic relationshipto standing pulse wave velocity has an r-squared value of 0.55 for anexponential fit of 3.333e^(0.0114x). The non-linear increase in wavespeed with increasing central systolic pressure is expected based onphysiologic loading of the arterial wall, yet since arterial stiffnessis an independent central measurement, the data offers two indicationsof cardiovascular function (e.g. arterial stiffness and centralpressure) as a method to manage hypertension. FIG. 17A is a graph of thecentral pulse pressure (e.g. central systolic minus central diastolicpressure) obtained using a SphygmoCor arterial tonometer for a group ofindividuals. FIG. 17B is a graph of the standing pulse wave velocityconsistent with embodiments of the present disclosure versus the centralpulse pressure. The central pulse pressure relationship to standingpulse wave velocity has an r-squared value of 0.56 for a linear fit(slope 0.2241, intercept 4.4975). The linear increase in wave speed withincreasing central pressure is expected based on physiologic loading ofthe arterial wall, yet since arterial stiffness is an independentcentral measurement the data offers two indications of cardiovascularfunction (e.g. arterial stiffness and central pressure) as a method tomanage hypertension. Surprisingly, the standing position alters thehemodynamic loads on the arteries in such a manner, compared to sittingand lying down, where all the aforementioned observations andcorrelations were identified. Therefore, while several systems exist andare capable of producing T1 signals that relate in time to the carotidpulse timing, the subsequent arterial stiffness measurements will bealtered based on the posture in which the recordings were taken, thussuch systems will not determine equivalent measures of circulatoryfunction.

Suitability to determine central blood pressure.

U sing the standing/upright measurements, useful and surprisingcorrelations are produced when combining measurements (or estimates) ofcentral pressure with the standing arterial stiffness measurement—andpatient information such as age and gender. For instance, centralsystolic and central pulse pressures can be stratified with respect tostanding arterial stiffness measures and patient information to indicatepotential sources of hypertension—facilitating improved diagnosis andtreatment. The present disclosure also recognizes that it can be usefulto relate, in a calibrated accurate manner, peripheral blood pressure tothe desired central blood pressure (FIGS. 15-18). The calibrated(corrected) peripheral measurements may then be used to obtain thecorrelations as shown in FIGS. 15 and 18 without the need of an arterialtonometer or internal pressure catheter.

Without being limited by theory, it is believed that the standingposition alters the hemodynamic load on the arteries relative to sittingand lying positions. This change in load produces significant changesthe pulse transit time (FIG. 11), thus the measure of arterialstiffness. Therefore, aspects of the present disclosure are directedtoward BCG-based systems that take advantage of the properties ofarterial stiffness timings that are altered based on the posture inwhich the recordings were taken. The standing position also provides adifferent and particularly relevant physiologic loading for measurementof arterial stiffness. With the unexpected correlations discussedherein, diagnosis and management of the circulatory function and bloodpressure can be facilitated.

Various other differences in vascular characteristic indices for theseated position, compared to standing positions, are also used by thesystem to monitor or diagnose patients. For further informationregarding differences in measurements obtained in upright positions,when compared to a lying or sitting position, reference can be made toS. C. Davis et. al, “Active standing reduces wave reflection in thepresence of increased peripheral resistance in young and old healthyindividuals,” Journal of Hypertension, vol. 29, pp. 682-689, 2011, andto Giryon Kim, Ah-young Jeon, Jae-hee Jung, In-cheol Kim, Jae-hyung Kim,Byoung-cheol Choi, Gil-joong Kim, Yong-soo Seo, Dong-keun Jung,Soo-young Ye, and Gye-rok Jeon. 2007. Vascular Variation of PTT and theVascular Characteristic Index According to the Posture Change. InProceedings of the 2007 International Conference on ConvergenceInformation Technology (ICCIT '07). IEEE Computer Society, Washington,D.C., USA, 2426-2425, each of which is fully incorporated herein byreference.

The ability to measure central blood pressure in a simple andcost-effective manner is an on-going endeavor and the mainstream use ofcentral measurements are believed to be the next advance in clinicalhypertension (Kaplan, 2010, p. 37). In the absence of a central pressuremeasurements obtained from a device such as an arterial tonometer (orcatheter), the arterial stiffness measurement would only present onedimension of cardiovascular function. A peripheral pressure measurementwould not offer as much utility for hypertension management, asevaluation of anti-hypertensive drug effects from such a device canunderestimate the benefit by 20 mmHg (or greater) for systolic and 1-2mmHg for diastolic, compared to a central pressure measurement (Nichols& O'Rourke, 2005, p. 362). This underestimated benefit is a result ofamplification of the arterial pressure wave, which is a complexinteraction between pulse wave velocity, ejection duration and wavereflection of the lower extremities (Nichols & O'Rourke, 2005, p.360-363). FIG. 15 depicts a method to determine the central pressures,using a peripheral blood pressure measurement (e.g. a brachial bloodpressure cuff), user information and embodiments consistent with thepresent disclosure. The amplification effect is quantified with thescale-based system and then used to correct the peripheral measurement.FIG. 18A is a graph depicting the systolic pressure differences betweencentral measurements obtained using a SphygmoCor arterial tonometer anda peripheral brachial blood pressure measurement, which shows asignificant pressure difference. FIG. 18B is a graph depicting thesystolic pressure differences between central measurements obtainedusing a SphygmoCor arterial tonometer and amplification-correctedperipheral measurement, where the amplification-correction wasdetermined using embodiments consistent with the present disclosure. Theaverage pressure difference is zero mmHg and the standard deviation is3.18 mmHg for a population of individuals 20-79 years old. Using thisapproach, an individual can obtain both central pressure and vascularstiffness measurements in a practical manner, enabling hypertensivemanagement.

The following references provide various different supporting materialsand teachings and are each incorporated by reference in their entirety.

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The various embodiments described above are provided by way ofillustration, and should not necessarily be construed to limit thedisclosure. Based on the above discussion, those skilled in the art willreadily recognize that various modifications and changes may be made tothe present disclosure without strictly following the exemplaryembodiments and applications illustrated and described herein. Forexample, algorithms, calibration, and verification methods developed forthis system can be used for any BCG measurement system including bedsand tables. Other scale configurations may be implemented, such as aseated or prone configuration, with the scale held vertically or atother relative angles. Custom strain gauges can be used in lieu of ascale interfaced to the similar electronics as discussed herein. Severalalternative electronics configurations are used for various embodiments,some of which may include lock-in based circuits. Multiple scales can beused to mitigate or eliminate noise, such as by placing a scale can beplaced under each leg of a chair-based circuit, and by constructing alarger bridge circuit. A number of exemplary and experimentalimplementations are discussed in detail in the appendices attached inthe above-referenced provisional applications, which are fullyincorporated herein. The teachings of this disclosure include thoseteachings found in the appendices (A-G) for much of the above-noteddiscussion of example embodiments, and the various teachings can beimplemented either alone or in combination with one another. The skilledartisan would appreciate the contemplated context of the teachings foundin the appendices, e.g., in light of overlapping technical discussion.These and other modifications and changes do not depart from the truespirit and scope of the present disclosure.

What is claimed is:
 1. A bodyweight sensing apparatus comprising: abodyweight sensing scale; a first sensor included in or as part of thebodyweight sensing scale, and configured and arranged to capture acardiogram signal of a user from at least one foot of the user while theuser is in an upright position and with said at least one foot of theuser on the bodyweight sensing scale; a second sensor configured andarranged to capture a pressure pulse from a distal artery location thatis at or below a user's femoral artery while the user is standing on thebodyweight sensing scale; and logic circuitry configured and arranged togenerate an arterial pulse wave velocity of the user, wherein the logiccircuitry is further configured and arranged to respond to the firstsensor and to the second sensor by comparing timings corresponding tothe cardiogram signal and the pressure pulse, as respectively providedby the first sensor and to the second sensor, whereby the arterial pulsewave velocity is derived from the compared timings and is indicative ofarterial stiffness of the user.
 2. The apparatus of claim 1, furtherincluding another sensor, including circuitry configured to obtainheart-related signals from the user of the bodyweight sensing scale foruse by the logic circuity and also configured to wirelessly communicatewith the logic circuity.
 3. The apparatus of claim 1, wherein the logiccircuitry is configured and arranged to generate the arterial pulse wavevelocity based on portions of the cardiogram signal that are indicativeof a pressure pulse of an ascending portion of an aorta, the pressurepulse of the user at the distal artery location and a distance betweenthe aorta and the distal artery location, wherein the arterial pulsewave velocity is indicative of the biological or physiological aspectsrelating to the arterial stiffness.
 4. The apparatus of claim 1, whereinthe logic circuitry is configured and arranged to generate the arterialpulse wave velocity based on portions of the cardiogram signal that areindicative of a pressure pulse of an arch portion of an aorta, thepressure pulse of the user at the distal artery location and a distancebetween the aorta and the distal artery location, wherein the arterialpulse wave velocity is indicative of the biological or physiologicalaspects relating to the arterial stiffness.
 5. The apparatus of claim 1,further including a display configured to output a weight of the userwhile the user is standing on the bodyweight sensing scale, and aweight-sensing arrangement that includes circuitry and a set of forcesensors configured to provide indications of weight distribution acrossthe bodyweight sensing scale to the logic circuit.
 6. The apparatus ofclaim 1, wherein the second sensor is configured to capturephotoplethysmography characteristics of the distal artery location thatis at or below the user's femoral artery.
 7. The apparatus of claim 1,further including a tertiary circuit configured and arranged to detectan indication of at least one of noise present in the cardiogram signaland wherein the logic circuitry is configured to process the cardiogramsignal by removing the noise present in the cardiogram signal.
 8. Theapparatus of claim 7, wherein the cardiogram signal is a BCG(ballistocardiogram) signal and wherein the tertiary circuit includes anelectrocardiogram (ECG) sensor configured and arranged to detect an ECGsignal from the user and to provide an output characterizing thedetected ECG signal, and the logic circuitry is configured to use thetertiary circuit output to process the captured cardiogram signal byfiltering and averaging the cardiogram signal to generate a filtered BCGsignal.
 9. The apparatus of claim 1, wherein a plurality of pressuresensors are used in conjunction with a T1 signal to derive a centralaortic stiffness and a peripheral arterial stiffness from pulse timings.10. The apparatus of claim 1, wherein the logic circuitry is configuredto generate a ballistocardiogram signal by generating anensemble-average, or triggered moving average, of the cardiogram signalusing a detected photoplethysmography signal.
 11. The apparatus of claim1, further including a circuit arrangement integrated with hand-gripelectrodes coupled to the bodyweight sensing scale, the electrodes andcircuit arrangement being configured to detect at least one of anelectrocardiogram (ECG) or photoplethysmography characteristic of theuser.
 12. The apparatus of claim 1, further including a peripheral bloodpressure sensor; and the logic circuitry is configured to use an outputof the peripheral blood pressure sensor to calculate the centralpressures; to generate ballistocardiogram signals over time; and toprovide an indication of at least one of arterial stiffness andcentral/peripheral pressure difference.
 13. The apparatus of claim 11,further including a memory circuit that stores baseline data includingat least one of root mean square BCG (ballistocardiogram) data andensemble average BCG amplitude data, and the logic circuitry isconfigured to generate output BCG signals based upon the stored baselinedata.
 14. The apparatus of claim 1, wherein the first sensor isconfigured and arranged to capture a BCG (ballistocardiogram) signalfrom pressure exerted by said at least one foot of the user while theuser is standing on the bodyweight sensing scale; and wherein the logiccircuitry is further configured and arranged to generate the arterialpulse wave velocity of the user by comparing timings corresponding tothe BCG signal and the pressure pulse.
 15. The apparatus of claim 14,wherein the logic circuitry is configured to use changes in the user'scardiovascular characteristics and/or bodyweight over a period of timeuseful for determining a treatment for the user.
 16. The apparatus ofclaim 14, further including: a circuit arrangement integrated with adetachable component connected to the bodyweight sensing scale and isconfigured to detect a photoplethysmograph characteristic of the user,and wherein the logic circuitry is configured to generate BCG signalsover time and to provide an indication of at least one of arterialstiffness and central/peripheral pressure difference.
 17. The apparatusof claim 14, further including a circuit arrangement including circuitrythat is configured to generate an ECG signal using characteristicsdetected from the user, and wherein the logic circuitry is configured tomodify coefficients of a transform function used to generate a BCGsignal, based upon the ECG signal.
 18. A method comprising: capturing acardiogram signal, using a first sensor integrated included in or aspart of a bodyweight sensing scale, from at least one foot of a userwhile the user is standing on the bodyweight sensing scale; capturing,using a second sensor, a pressure pulse from a distal artery locationthat is at or below a user's femoral artery while the user is standingon the bodyweight sensing scale; and comparing timings corresponding tothe cardiogram signal and the pressure pulse to calculate arterial pulsewave velocity, and using the compared timings to indicate arterialstiffness of the user.
 19. The method of claim 18, wherein thecardiogram signal is a BCG (ballistocardiogram) signal, whereincapturing the cardiogram signal includes measuring variations indownward pressure exerted by the user's feet and includes capturing acardiogram T1 signal that is indicative of mechanical movement of bloodthrough a user's aorta, and wherein comparing timings includes using alogic circuit to calculate the arterial pulse wave velocity bycalculating timings corresponding to the T1 signal and a timing of thepressure pulse.
 20. A bodyweight sensing apparatus comprising: abodyweight sensing scale; a first sensor included in or as part of thebodyweight sensing scale, and configured and arranged to capture acardiogram signal of a user from at least one foot of the user while theuser is in an upright position and on the bodyweight sensing scale; asecond sensor configured and arranged to capture a pressure pulse from adistal artery location that is at or below a user's femoral artery whilethe user is standing on the bodyweight sensing scale; and circuitry,including a programmed logic circuit, configured and arranged to beresponsive to the first sensor and the second sensor, by comparingtimings corresponding to the cardiogram signal and the pressure pulse,and therefrom, deriving and outputting an indication of arterialstiffness.
 21. The bodyweight sensing apparatus of claim 20, wherein thefirst sensor and the circuitry are configured and arranged to capturethe cardiogram signal and derive the indication of arterial stiffnessbased on calibrated parameters, including a limited frequency responseof circuits integrated with the first sensor for capturing thecardiogram signal and limited mechanical bandwidth attributable tostiffness and damping.